Databricks Certified Machine Learning - Associate
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Ultimate access to all questions.
What is the main benefit of using parallel processing for hyperparameter tuning?
A
It enhances the model's accuracy by carefully selecting each hyperparameter.
B
It decreases the dataset's complexity, making it easier to process.
C
It accelerates the tuning process by testing several configurations at the same time.
D
It guarantees the correct deployment of the model.
E
None of the above